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DBMS > Amazon SimpleDB vs. Atos Standard Common Repository vs. Microsoft Access vs. Spark SQL vs. YDB

System Properties Comparison Amazon SimpleDB vs. Atos Standard Common Repository vs. Microsoft Access vs. Spark SQL vs. YDB

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSpark SQL  Xexclude from comparisonYDB  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Spark SQL is a component on top of 'Spark Core' for structured data processingA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelKey-value storeDocument store
Key-value store
Relational DBMSRelational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websiteaws.amazon.com/­simpledbatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.microsoft.com/­en-us/­microsoft-365/­accessspark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdocs.aws.amazon.com/­simpledbdeveloper.microsoft.com/­en-us/­accessspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperAmazonAtos Convergence CreatorsMicrosoftApache Software FoundationYandex
Initial release20072016199220142019
Current release17031902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Scala
Server operating systemshostedLinuxWindows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Linux
Data schemeschema-freeSchema and schema-less with LDAP viewsyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or datenooptionalyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnono
Secondary indexesyes infoAll columns are indexed automaticallyyesyesnoyes
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardSQL-like DML and DDL statementsSQL-like query language (YQL)
APIs and other access methodsRESTful HTTP APILDAPADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages with LDAP bindingsC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnonoyes infosince Access 2010 using the ACE-enginenono
Triggersnoyesyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationSharding infocell divisionnoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnonenoneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationAtomic execution of specific operationsACID infobut no files for transaction loggingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)LDAP bind authenticationno infoa simple user-level security was built in till version Access 2003noAccess rights defined for Yandex Cloud users

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More resources
Amazon SimpleDBAtos Standard Common RepositoryMicrosoft AccessSpark SQLYDB
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